Pull Request Latency Explained: An Empirical Overview
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Abstract (arXiv)
Pull request latency evaluation is an essential application of effort evaluation in the pull-based development scenario. It can help the reviewers sort the pull request queue, remind developers about the review processing time, speed up the review process and accelerate software development. There is a lack of work that systematically organizes the factors that affect pull request latency. Also, there is no related work discussing the differences and variations in characteristics in different scenarios and contexts. In this paper, we collected relevant factors through a literature review approach. Then we assessed their relative importance in five scenarios and six different contexts using the mixed-effects linear regression model. We find that the relative importance of factors differs in different scenarios, e.g., the first response time of the reviewer is most important when there exist comments. Meanwhile, the number of commits in a pull request has a more significant impact on pull request latency when closing than submitting due to changes in contributions brought about by the review process.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Aug 2021.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 0; 2025: 0; 2026: 3.
6 papers.
- 2021On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requestscited by 6
- 2026Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHubcited by 6
- 2023Predicting the First Response Latency of Maintainers and Contributors in Pull Requestscited by 3
- 2023Understanding the Helpfulness of Stale Bot for Pull-based Development: An Empirical Study of 20 Large Open-Source Projectscited by 2
- 2026Rethinking Code Review in the Age of AI: A Vision for Agentic Code Reviewcited by 1
- 2026Govern the Repository, Not the Agent: Measuring Ecosystem-Level Risk in AI-Native Softwarecited by 0
- 2026Govern the Repository, Not the Agent: Measuring Ecosystem-Level Risk in AI-Native Software26 Jun 2026
- 2026Rethinking Code Review in the Age of AI: A Vision for Agentic Code Review17 May 2026
- 2026Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub1 Jan 2026
- 2023Predicting the First Response Latency of Maintainers and Contributors in Pull Requests13 Nov 2023
- 2023Understanding the Helpfulness of Stale Bot for Pull-based Development: An Empirical Study of 20 Large Open-Source Projects29 May 2023
- 2021On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests28 Oct 2021